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Real-time Superpixel Segmentation by DBSCAN Clustering Algorithm
% This is the matlab re-implementation code of the algorithm in the TIP16 paper. % You should compile the cpp file using visual studio 2008 or later version % -- mex DBscan_mex.cpp % Please run the demo code "demo_DBSCAN.m". %====================================================================== % If you are using this code in your publication, % please cite our paper, Thanks. %====================================================================== % J. Shen, X. Hao, Z. Liang, Y. Liu, W. Wang, and L. Shao, % Real-time Superpixel Segmentation by DBSCAN Clustering Algorithm, % IEEE Trans. on Image Processing, 25(12):5933-5942, 2016 %====================================================================== % Any further questions, please send email to: [email protected] or [email protected] %======================================================================
When we specify 100 superpixels, this code cannot run for many images in BSDS500:
e.g.
100039.jpg, 101027.jpg, 107045.jpg, .....
Hi, @shenjianbing @ahban @pmixer thanks for your great contribution to the open-sourced repo, very nice work.
Say I am using it to get super-pixel segmentation result for large image, e.g. 4k(3840x2160), which parameter shall I to modify for correct processing, I have already encountered some errors
// In function DBscan
int *neighb = new int[5000];
for(int i=0; i<5000; ++i) neighb[i]=0;
when the size of 'neighb` is 5000, I got the following error info
malloc: Incorrect checksum for freed object 0x7fb43011c200: probably modified after being freed
and when I change it to 500000 it works well, but the final segment result still not very good.
Solution refered to stackoverflow Malloc Error: incorrect checksum for freed object
So I am wondering which param I can change for clustering or merging stage to get as good result as expected?
Any suggestion would be appreciated! Much thanks!
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